Personalising treatment of diabetic complications with a focus on A potential role for the gut microbiota in diabetic kidney complications
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1 Personalising treatment of diabetic complications with a focus on A potential role for the gut microbiota in diabetic kidney complications Peter Rossing MD DMSc University of Copenhagen Steno Diabetes Center
2 Disclosures 1 Professor Rossing has received the following: consultancy and/or speaking fees (to his institution) from AbbVie, Astellas, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lilly, MSD, Novo Nordisk and Sanofi Aventis research grants from AbbVie, AstraZeneca and Novo Nordisk
3 Diabetes is a leading risk factor for renal impairment Chart Title 2,0% 2,3% 17,5% Diabetes High blood pressure Glomerulonephritis Cystic diseases Urologic diseases Other US Renal Data System 2007 Annual Data Report: Atlas of Chronic Kidney Disease and End-Stage Renal Disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD.
4 Hospital days/100 patient years Costs of complications in patients with diabetes: the Helsinki Study Without complications With complications x Excess cost of T2D Mean excess costs of healthcare of people with diabetes (and without complications) by type of diabetes Excess costs of T1D Finnish Diabetes Association. DEHKO Finnish Diabetes Association 2001
5 Proteinuria Is an Independent Risk Factor for Mortality in Type 2 Diabetes Survival (all-cause mortality) Normoalbuminuria (n=191) Microalbuminuria (n=86) Macroalbuminuria (n=51) Years P<0.01 normo vs. micro- and macroalbuminuria P<0.05 micro vs. macroalbuminuria Gall, MA et al. Diabetes 1995;44:1303
6 Proteinuria based prevention of DM nephropathy Albuminuria RAS-inhibition
7 RENAAL: Effects of Losartan on renal and CVD in type 2 diabetes and nephropathy The unmet need Brenner et al NEJM 2001
8 Glomerular filtration rate (ml/min) Natural history of diabetic nephropathy Glomerular filtration rate Urinary protein excretion Pre-stage Incipient diabetic Overt diabetic End-stage nephropathy nephropathy renal disease Years Urinary protein excretion (mg/day) Johnson & Feehally, eds. Comprehensive Clinical Nephrology, 2000 New and early markers New treatments
9 Unbiased (open) search for new markers 8 Single marker strategy
10 OMICS: from genes to metabolites GENOME DNA What is possible TRANSCRIPTOME mrna What appears to be happening PROTEOME PROTEINS What makes it happen METABOLOME METABOLITES What is happening CISCNCANCER.ORG
11 Proteomic utility in DN 10 Add to our understanding of patho-physiology Identify patients at risk Monitor progression of disease and treatment efficacy May identify new treatment targets
12 CE-MS proteomic technique - High separation power and sensitive detection 11 Urine sample Separation and analysis of proteins and peptides (>1,000) Run time ~60 min Capillary electrophoresis Mass spectrometry Data evaluation CE fast robust inexpensive reproducible MS resolution scan speed Contrib Nephrol. 2008; 160:
13 Proteomic profile: T1DM +/- DN 12 Control Normo Micro Macro K Rossing et al., JASN, 2008
14 Pathosphysiological suggestions Apoptosis/chronic inflammation (ROS, AGE) Acute phase response u-a1at Inhibition of plasmin Inhibition of fibrinolysis u-fiba Glomerular fibrin deposition u-b2mg u-albu Renal damage u-collagens Inhibition of matrix metalloproteases (e.g. MMP2 and MMP9) u-plasma proteins - Increased collagen accumulation - Reduced degradation of collagens - Excessive accumulation of ECM Renal fibrosis Reduced renal function / proteinuria Decrease of GFR
15 Monitoring Treatment Effects by Irbesartan in microalbuminuric type 2 DM 14 S Andersen et al BMC Nephrol 2010
16 Prediction 15 Longitudinal analysis of non-progressors and progressors to DN Classification factor AER [ 킽 /min] Classification factor AER [ 킽 /min] Proteome analysis and AER from diabetic normoalbuminuric patients (151 samples), assessed for progression to DN over 5 years 100 Month Month 0 80 Sensitivity AER µg/min CKD model AUC 95% CI AER [µg/min] to CKD model to Specificity Zü rbig et al Diabetes 2012
17 CKD273 and progression to microalbuminuria 100% Event rate (Microalbumin uria) 80% 60% 40% 20% High-risk Low-risk P= Time from randomisation (y) 0% High-risk, n (events, n) 74(0) 69(12) 58(13) 53(16) 35(19) 6(19) Low-risk, n (events, n) 666(0) 650(25) 610(45) 570(63) 465(68) 82(72) MK Lindhardt et al Neph Dial Trans 2016
18 The Priority Trial Type 2 DM Normoalbuminuria High-risk n ~ 250 Proteomic test Low-risk n ~ 1700 Randomised Double-blinded Placebo controlled Observational Placebo Spironolactone Three years follow-up
19 Targets in Diabetic Nephropathy Oxidative stress NOX1/4i Systemic Blood Pressure AII, ET1,Renin, Aldo Proteinuria soludexide Glycemic control DPP4, GLP1, SGLT2,PPARγ Glycation AGEi, RAGE blockers PKCi Growth factors CTGF/TGFb/VEGF Ab Dietary protein intake Smoking Uric Acid Vitamin D VDRA Hyperlipidemia Statin? Fibrate? Inflammation CCR2/CCR5 (CCX140, NOXON), Pentoxilfyllin, Nrf, JAK/STAT (Baricitinip)
20 Cumulative probability of event (%) EMPA-REG OUTCOME Incident or worsening nephropathy Hazard ratio, 0.61 (95% CI, ) P<0.001 Empagliflozi n Placebo Month No. at Risk Empagliflozin Placebo Wanner C et al. N Engl J Med 2015; 375: CI, confidence interval
21 Time to first renal event Macroalbuminuria, doubling of serum creatinine, ESRD, renal death The cumulative incidences were estimated with the use of the Kaplan Meier method, and the hazard ratios with the use of the Cox proportionalhazard regression model. The data analyses are truncated at 54 months, because less than 10% of the patients had an observation time beyond 54 months. CI: confidence interval; ESRD: end-stage renal disease; HR: hazard ratio. Presented at the American Diabetes Association 76 th Scientific Sessions, Session 3-CT-SY24. June , New Orleans, LA, USA.
22 PROTON PeRsOnalising Treatment Of diabetic Nephropathy Moving from albuminuria to multidimensional characterisation and intervention Sponsored by Novo Nordisk Foundation
23 From albuminuria to profile-omics Albuminuria RAS-inhibition Personalised Treatment
24 Extreme cases 23
25 Pilot studies, based on target/intervention 24 weeks treatment Placebo Liraglutide NEW DRUG Liraglutide NEW DRUG Placebo week 12 week 24 End of study UAER: Randomization, week 12 and week 24 24h BP: Randomization, week 12 and week 24 Kidney function ( 51 Cr GFR): week 12 and week 24 Markers of inflammation: Randomization, week 12 and week 24 Potential targets: fibrosis, glucose inflammation, oxidative stress RAS/bradykinins Microbiome (diet, probiotica, adsorption) etc.
26 GUT MICROBIOTA 25 From Frontiersin.org
27 R References A Ramezani et al Am J Kid Dis
28 Symbiotic gut microbiota 27 R References A Ramezani et al Am J Kid Dis 2016
29 Dysbiotic CKD gut microbiota 28 R References A Ramezani et al Am J Kid Dis 2016
30 LPS induces progression of diabetic nephropathy in type 1 DM 29 References Nymark et al Diabetes Care 2009
31 LPS acting via TLR pathway 30 References P Saurus et al Cell Death Dis. 2015
32 Indoxyl Sulfate related to GFR 31 References FC Barreto et al Clin JASN 2009
33 Structural features of AST-120 and activated charcoal (United States Pharmacopeia). Gerald Schulman et al. JASN 2015;26: by American Society of Nephrology
34 Gastrointestinal binding of Indoxyl Sulfate with AST References G Schulman et al Am J KidDis 2006
35 AST 120 reducing loss of GFR in CKD 34 References Akizawa T et al Am J Kid Dis 2009
36 Gerald Schulman et al. JASN 2015;26: EPPIC trial of AST-120 in CKD
37 TMAO cause platelet hyperreactivity 36 References W Zhu et al Cell 2016
38 TMAO and CKD 37 References W. H. Wilson Tang, 1,2 Circ Res Jan 30; 116(3):
39 TMAO induce renal damage in experimental setting 38 References W. H. Wilson Tang, 1,2 Circ Res Jan 30; 116(3):
40 References A Ramezani et al Am J Kid Dis
41 Modification of Gutmicrobiota 40 Antibiotics
42 Personalised treatment in the future n ~? High-risk profile Randomised Double-blinded Placebo controlled Omics Low-risk Observational Targeted intervention follow-up
43
44
45 Steno Diabetes Center My Steno web-based diabetes care
46 Survival Probability Steno-2 post-trial: Sustained effect of multifactorial intervention Kaplan-Meier Estimates Survival Intensive Conventional HR 0.55 p = Number at risk: Intensive Conventional 7.9 years Years since randomization Gæ de P, Ø lgaard J et al Diabetologia 2016; Epub ahead of print
47 Ali et al. N Engl J Med 2013;368:
48 Conclusion Diabetic nephropathy remains a major challenge New treatments are needed, new targets necessary Systems medicine with multidimensional characterisation can identify targets and select patients for interventions Gut microbiota may be both a target and a culprit Personalising treatment may optimise efficacy and reduce adverse events, thereby improving outcome for patients
49 Thanks to collaborators and colleagues
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